1. Field of the Invention
Embodiments of the present invention relate to systems and methods for prescription or pharmaceutical compound verification. More particularly, embodiments of the present invention relate to systems and methods for pharmaceutical verification using machine vision and spectroscopic analysis.
2. Background Information
Most states in the U.S. require that a registered pharmacist confirm whether a pharmaceutical delivered to a customer is indeed the pharmaceutical prescribed by the physician. A part of this confirmation is accomplished by the pharmacist visually inspecting the dispensed pharmaceutical to verify its correctness. In fact, pharmacists can spend as much as 50% of their time verifying prescriptions.
Despite the verification process, errors are not uncommon, especially during peak operating hours. For example, according to the National Association of Boards of Pharmacy, as many as 5% of the 3 billion prescriptions filled each year are incorrect. These erroneous prescriptions are responsible for as many as 7,000 deaths annually in the United States. Further, due to a steadily decreasing number of pharmacists, and an expected increase in the annual demand for prescriptions to nearly 5 billion, the number of instances in which a customer receives the wrong medication is anticipated to increase.
Not surprisingly, increasing prescription errors have resulted in a growing collection of consumer complaints about potentially serious errors such as wrong counts, wrong drugs, and/or wrong drug strengths. Drug strength is, for example, a quantification of the concentration or potency of the active ingredient of the drug. Thus, there is a strong need for a system to replace the present manual verification technique and to allow the verification and validation steps to be performed automatically and more reliably. A by-product of such an automatic verification system is freeing up pharmacists' time so they can provide better service to their customers.
Several conventional semi-automated prescription verification techniques have been developed to minimize errors associated with manual prescription verification. For example, conventional semi-automatic visual verification techniques rely on the pharmacists comparing an electronic image of the prescribed medication, i.e., a picture of the prescribed medication retrieved from a data library, to the actual medication that is to be dispensed to a customer. However, the visual difference between pharmaceuticals may be so subtle that errors are likely to occur even when comparing the contents of the prescription vial to a picture on a computer screen.
More objective and automated visual recognition techniques have also been applied to prescription verification. Such techniques use an imaging device and image processing algorithms to produce what is often referred to as machine vision. For example, U.S. Pat. No. 6,535,637 to Wootton et al. describes obtaining an image of the contents of a pharmaceutical container through the open top of the container, processing the image to isolate a pill, processing the image of the pill to extract a characteristic such as color, shape, size, finish, texture, or surface properties, and comparing the characteristic to known characteristics to identify the pill.
Spectroscopic techniques have also been used to verify dispensed pharmaceuticals. Spectroscopic techniques rely on the unique spectral signature exhibited by each pharmaceutical, such as a pill, tablet, capsule, gelcap, gel, and liquid. Representative, non-limiting spectroscopic techniques for pharmaceutical verification include Near-Infrared (NIR) spectroscopy, ultraviolet (UV) and visible spectroscopy, Raman spectroscopy, and Fourier Transform Infrared (FT-IR) spectroscopy.
Both machine vision and spectroscopic techniques of pharmaceutical verification have advantages and disadvantages. For example, a machine vision technique is likely to be fooled by counterfeit pharmaceuticals, while a spectroscopic technique is unlikely to have trouble spotting a counterfeit. Similarly, a spectroscopic technique might not be able to distinguish different strengths of the same pharmaceutical, while a machine vision technique can determine the different strengths by the shapes of the pills.
In view of the foregoing, it can be appreciated that a substantial need exists for systems and methods that can perform pharmaceutical verification using both machine vision and spectroscopic analysis.